Computer graphics and image processing tutorial

Computer graphics applications

In general, autonomous segmentation is one of the most difficult tasks in digital image processing.
A rugged segmentation procedure brings the process a long way toward a successful solution of imaging problems that require objects to be identified individually..

Features of computer graphics

It is an essential preprocessing step in many applications, such as face recognition, object detection, and image compression.
Image processing is done to enhance an existing image or to sift out important information from it..

Features of computer graphics

Step 1: Image Acquisition.
The image is captured by a sensor (eg. Step 2: Image Enhancement. Step 3: Image Restoration. Step 4: Colour Image Processing. Step 5: Wavelets. Step 6: Compression. Step 7: Morphological Processing. Step 8: Image Segmentation..

How to learn image processing?

111 Steps to Start with Image Processing.
OpenCV and Python: the basics of the super-popular image processing library.

1. Install OpenCV.
To install the OpenCV Python 3 API we can simply use pip.
2. Import images
3. Read an image
4. Rearrange channels: from BGR to RGB
5. Show the channels separately
6. Visualize histograms
7. Extract bit depth

What are the steps involved in dip?

Step 1: Image Acquisition.
The image is captured by a sensor (eg. Step 2: Image Enhancement. Step 3: Image Restoration. Step 4: Colour Image Processing. Step 5: Wavelets. Step 6: Compression. Step 7: Morphological Processing. Step 8: Image Segmentation..